1. Field of the Invention
The present invention relates to an image coding device, method and program to compress moving images.
2. Related Art
Conventionally, block coding such as block DCT (Discrete Cosine Transform) coding has been known as a coding method to efficiently compress still image data, moving image data and the like.
When image data is compressed or decompressed by such block coding, block distortion may occur. The higher a compression rate is, the more likely the distortion occurs. Since the DCT coding and the like makes conversion in a closed space in a block without considering correlation between blocks across a block boundary, block continuity cannot be retained at the boundary. Thus, the difference of a restored data value at the boundary with an adjacent block is recognized as the block distortion. Additionally, if high-frequency components are removed to raise a compression rate, the continuity cannot be retained at the boundary with the adjacent block, causing the distortion. The block distortion, which occurs when the block coding is performed on image data, is more easily to be recognized than usual random noises because it has a kind of regularity. And it is a main cause of image quality degradation.
To reduce this block distortion, for example, a document of “A denoising filter in an MC-DCT coding method”, Ida and Dachiku, IEICE (The Institute of Electronics, Information and Communication Engineers) 1990 Shunki Zenkoku Taikai Koen Ronbun-shu (in Japanese) (Spring National Convention Lectures Transactions) 7-35 discloses a technique of using a quantization step size to decide filter ON/OFF, or executing a multiple courses of processing by changing a processing direction to retain edges and perform denoising. Although in this method it is easy to perform the processing, there is a disadvantage that the image's high-frequency components are lost and resolution is degraded.
Additionally, a document of “Characteristics of adapted denoising filters in image block coding”, Izawa, Kiyo (in Japanese) (Annals) No. 74, pp. 89-100, Faculty of Engineering, Shinshu University discloses a technique of performing the DCT even on surrounding blocks and removing noise frequency components. Although this method effectively reduces block distortion while maintaining resolution, the processing is complex and expensive, so it is unsuitable to apply to some devices, especially consumer devices.
While the above methods are techniques used in decoding images, many other techniques have been proposed. However, with reducing the block distortion at the decoding, erroneous determination of the block distortion or pseudo-edges of the blocks can occur. To resolve this problem, as a method to make the block distortion as unremarkable as possible at the encoding, the Japanese Patent Laid-Open No. 8-130735 proposes a method for specifying a different reference coordinates position for block splitting for each frame to shift the block distortion for each frame to make the distortion unremarkable. In this method, however, since encoding and decoding are a pair in an algorithm, the opportunity to apply the algorithm is significantly limited.
Additionally, the Japanese Patent Laid-Open No. 2001-268580 proposes a method for using motion vectors to encode parts remarkable in motion with high-frequency components reduced to raise the compression rate, and encode parts unremarkable in motion without highly reducing high-frequency components to retain resolution. This method, however, has a problem that since it assumes that the motion vectors are correctly detected, image quality drops if the motion vectors are falsely detected.
Incidentally, one example of block coding methods for image data may include the MPEG (Moving pictures Experts Group) scheme in which the DCT using correlation inside an image, motion compensation using correlation between images, and the Huffman coding using correlation between code strings are combined.
The MPEG scheme accomplishes the compression by reducing high frequency components of space frequency of image data by weighting quantization. Thus, there is a problem that if raising the compression rate is attempted, the high frequency components are removed accordingly and block distortion occurs. Additionally, if high frequency components are sufficiently reduced when image data is input, high frequency components removed afterward by the quantization decrease and the distortion due to the compression reduces. If, however, too many high frequency components are lost at the input, a restored image looses sharpness, making a blurred image. This seriously affects, especially, images unremarkable in motion.